Every day, several quintillion bytes of data may be created around the world. These data may come from various sources, e.g., posts to social media sites, digital pictures and videos, purchase transaction records, bank transactions, sensors used to gather data and intelligence (like weather information), cell phone Global Positioning System (GPS) signals, and many others. This type of data and its accumulation may be referred to as “big data.” This large amount of data eventually may be stored and maintained in storage nodes, such as hard disk drives (HDDs), solid-state storage drives (SSDs), or the like, and these may reside on networks or on storage accessible via the Internet, which may be referred to as the “cloud.” In some cases the data is not accessed very frequently but it may be advantageous for it to be available at any time with reduced or minimal delay. For example, the data may be write once, read many (WORM) data, such as data posted to social media web sites, or video media posted by users on public video sharing sites.
Some queries, or requests for data from storage nodes may be time-sensitive (i.e., it may be advantageous for data to be delivered quickly in response to such requests) and some may not be time-sensitive (i.e., there may be little advantage to delivering the data quickly. Retrieving data may in some circumstances involve causing a storage device to transition from a power save mode to a normal mode of operation; such transitions may be avoided or postponed without significant disadvantage when the request for data is not time-sensitive.
Thus, there is a need for a system and method of executing queries that avoids or postpones transitions from power save mode for queries that are not time-sensitive.